Forecasting crude oil returns with oil-related industry ESG indices

Kaixin Li, Zhikai Zhang, Yudong Wang and Yaojie Zhang

Journal of Commodity Markets, 2024, vol. 36, issue C

Abstract: We construct North American oil-related industry ESG indices based on Elastic Net and PCA/SPCA/PLS dimensionality reduction techniques. We discover that the ESG indices show significant forecasting power for crude oil returns both in- and out-of-sample, and their ability to significantly predict oil returns remains when the delayed ESG release is considered. Additionally, our analysis suggests that the predictive abilities of ESG indices remain robust and unaffected by stock returns in the oil-related industry. The ESG indices can provide information that is heterogeneous and complementary to macroeconomic variables and technical indicators. Based on the analysis over the business cycle, ESG indices show predictability in forecasting crude oil returns during economic expansions rather than recessions. Moreover, ESG indices' predictive ability is also of economic significance, as shown by the substantial economic value it generates for mean-variance investors. Finally, we explore the potential economic channels, and the result reveals that the predictive power of ESG indices arises from speculative behavior in the oil market and oil demand.

Keywords: ESG indices; Crude oil returns; Elastic net; Economic expansions; Speculative behavior (search for similar items in EconPapers)
JEL-codes: C32 C53 G17 Q47 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jocoma:v:36:y:2024:i:c:s2405851324000631

DOI: 10.1016/j.jcomm.2024.100444

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